We accidentally solved robotics by watching 1M hours of YouTube

Pure vision will never be enough because it does not contain information about the physical feedback like pressure and touch, or the strength required to perform a task.

For example, so that you don't crush a human when doing massage (but still need to press hard), or apply the right amount of force (and finesse?) to skin a fish fillet without cutting the skin itself.

Practically in the near term, it's hard to sample from failure examples with videos on Youtube, such as when food spills out of the pot accidentally. Studying simple tasks through the happy path makes it hard to get the robot to figure out how to do something until it succeeds, which can appear even in relatively simple jobs like shuffling garbage.

With that said, I suppose a robot can be made to practice in real life after learning something from vision.

> Pure vision will never be enough because it does not contain information about the physical feedback like pressure and touch, or the strength required to perform a task.

I'm not sure that's necessarily true for a lot of tasks.

A good way to measure this in your head is this:

"If you were given remote control of two robot arms, and just one camera to look through, how many different tasks do you think you could complete successfully?"

When you start thinking about it, you realize there are a lot of things you could do with just the arms and one camera, because you as a human have really good intuition about the world.

It therefore follows that robots should be able to learn with just RGB images too! Counterexamples would be things like grabbing an egg without crushing, perhaps. Though I suspect that could also be done with just vision.